Algorithm 1. Multi-objective grey wolf optimizer (MOGWO).

Begin

Initialize the grey wolf population $X_i\left(i=1,2,\cdots ,P\right)$

Initialize $a, A$ and $C$

Calculate the objective values of each wolf, put the non-dominated solutions into the archive

Select the best three wolves from the archive and save as $\alpha ,\beta$ and $\delta$

g = 1

while (g < maximum number of iterations)

for each wolf

Update the position by Equations (16)–(22)

end for

Update $a, A$ and $C$

Calculate the objective values of each wolf, update the archive

Update $\alpha ,\beta$ and $\delta$

g = g + 1

end while

Return archive